基于受控马尔科夫链的软件缺陷优化测试策略

Optimal Testing for Software Defects Based on Controlled Markov Chain

目前许多文献都讨论的受控马尔科夫链软件测试模型,是通过对部分假设条件进行特殊化处理后得到的,这将导致模型的适用范围较小且偏离实际应用。依据软件控制论思想,通过一系列新的制约条件的转换,提出一种改善的、测试资源约束下的受控马尔科夫链模型来消除已有模型的缺陷。同时,该模型能够在高效性、复杂性和适用性3方面达到一个平衡点。为了证明其有效,根据该模型设计了一种新的软件缺陷优化测试策略,并对该策略进行了仿真实验,将其与传统的随机测试策略进行了比较。实验结果表明,该模型具有较高的实用性和有效性。

The Controlled Markov Chain（CMC） model for software testing discussed in most works at present is obtained from a series of assumptions,and partial of the assumptions have been specialized,which makes the scope of application of these models were comparatively small.And thus these models deviate from practical application.According to the software cybermetics,this article provided an improved CMC model with cost constraints by introducing a series of new transformation of limit condition.This model eliminates some of the defects of existing models.Meanwhile,the model can reach a balance in efficiency,complexity and applicability.In order to verify the effectiveness of the model,a new optimal testing strategy for software defects was designed according to the newly provided model.Through a simulation experiment,the strategy was compared with the traditional random testing strategy.The results show that our improved CMC model has high applicability and effectiveness.